(Re)conceptualizing Integration: An Arts-Informed Study of Kurdish-Turkish Asylum Claimants’ Post-Migration Experiences in Canada
Bibliographic record
Abstract
The number of Turkish and Kurdish refugee claimants to Canada has been increasing significantly over the last six years. Despite this increase, there are limited studies that focus on the post-migration experiences of Turkish and Kurdish individuals from refugee backgrounds in Canada. Although policies highlight that knowledge of the host society's language(s) is a key indicator of successful integration, little attention has been paid to the role of power relations, opportunities for social interaction, language practice and marginalization experiences in shaping the language learning experiences of migrants. Thus, my study aims to answer the following research questions: (a) How do individuals from refugee backgrounds perceive and experience “integration?” (b) What are the challenges of learning languages in Canada as an individual from a refugee background? (c) What opportunities or successes do individuals from refugee backgrounds experience while learning languages in Canada?Within the context of a participatory arts-informed multiple case study, I worked with ten Kurdish and Turkish youth between the ages of 18-30 who participated in semi-structured interviews and online focus groups. During the focus groups, participants produced and shared different (art)ifacts, such as music performance, sculptures, poems, photographs, etc. on diverse topics such as identity, language learning experiences, and involvement in community programs. Engaging in critical group dialogues, participants identified their needs, concerns, and opportunities and proposed solutions for stakeholders in the resettlement and education sectors. Findings revealed that participants’ intersecting identities and their marginalization experiences resulting from different forms of systemic oppression shaped their language learning and “integration” experiences in Canada. Their language learning trajectories were shaped by multilevel structural factors, ideologies and their own perceptions of their languages and position in Canada. Findings also revealed participants’ resilience and resistance to being understood as “lacking agency” as they created and sought opportunities for personal, academic, and language development to move towards a pathway to post-secondary education. I describe implications for language programs for newcomers and policies related to resettlement and language education and, in particular, the need to shift from measuring settlement success by considering integration to making inclusion a priority.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.042 | 0.022 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".